Medical professionals utilize a variety of imaging techniques to generate images of internal features of humans, animals, and other objects. For example, three dimensional (“3D”) images generated via volume rendering are useful for understanding spatial dimensions of internal features. Volume rendering may involve ray-casting in which virtual rays are cast through a volume data set, and points along the rays are sampled for image generation purposes. Ray-casting is one of the most popular rendering techniques used to generate the highest quality images. However, as volume data sets increase in size, the number of sampling rays or amount of interpolation also increase. Consequently, processing of the information degrades due to intensive computation and memory access. The degradation is even more problematic during interactive modes where the displayed image is being rotated or shifted by a medical professional for viewing.
To increase rendering speed, especially during interactive mode, a smaller image (lower resolution) is rendered and then is scaled in a two-dimensional (“2D”) plane to the appropriate resolution. However, reducing the image resolution in each dimension may result in poor image quality.
Image-space adaptive sampling is another approach to increase rendering speed. In this method, image space is divided into sub-regions (tiles). A number of low density sampling rays are cast through a volume data set, one for each region. An algorithm determines whether to cast more rays or perform 2D interpolation for a given region. For each region, the determination is based on whether an object is indicated along the cast ray for the region. However, fine features, such as vessels and bronchioles, may be missed, which tends to blur the image.